Differential Privacy

DPED: Multi-Layer Noise Distillation for Privacy-Preserving Text Embeddings EMNLP 2025 DP-MemArc: Differential Privacy Transfer Learning for Memory Efficient Language Models AAAI 2025 Dyn-D^2P: Dynamic Differentially Private Decentralized Learning with Provable Utility Guarantee IJCAI 2025 Enhancing Feature-Specific Data Protection via Bayesian Coordinate Differential Privacy AISTATS 2025 Enhancing Learning with Label Differential Privacy by Vector Approximation ICLR 2025 Enhancing Privacy in the Early Detection of Sexual Predators Through Federated Learning and Differential Privacy AAAI 2025 Exploiting Hidden Symmetry to Improve Objective Perturbation for DP Linear Learners with a Nonsmooth L1-Norm ICLR 2025 Federated Binary Matrix Factorization Using Proximal Optimization AAAI 2025 Federated Graph Condensation with Information Bottleneck Principles AAAI 2025 FLIPHAT: Joint Differential Privacy for High Dimensional Linear Bandits AISTATS 2025 Gaussian Differentially Private Human Faces Under a Face Radial Curve Representation ICLR 2025 General Staircase Mechanisms for Optimal Differential Privacy AISTATS 2025 Global Group Fairness in Federated Learning via Function Tracking AISTATS 2025 How Private are Language Models in Abstractive Summarization? EMNLP 2025 Inspecting the Representation Manifold of Differentially-Private Text NAACL 2025 Investigating User Perspectives on Differentially Private Text Privatization NAACL 2025 Learning from End User Data with Shuffled Differential Privacy over Kernel Densities ICLR 2025 Leveraging Semantic Triples for Private Document Generation with Local Differential Privacy Guarantees EMNLP 2025 Locally Private Estimation with Public Features AISTATS 2025 Locally Private Sampling with Public Data AISTATS 2025 Multi-level Certified Defense Against Poisoning Attacks in Offline Reinforcement Learning ICLR 2025 Near-optimal algorithms for private estimation and sequential testing of collision probability AISTATS 2025 Noise-Aware Differentially Private Variational Inference AISTATS 2025 On Consistent Bayesian Inference from Synthetic Data JMLR 2025 On the Inherent Privacy of Zeroth-Order Projected Gradient Descent AISTATS 2025